Compare Q>=3 and Q>=4 Datasets

Participant Table, Q>=4

## 
## 
## |                      | level  |          ASD          |           TD           |   p    | test |
## |:-------------------------:|:------:|:---------------------:|:----------------------:|:------:|:----:|
## |           **n**           |        |          28           |           27           |        |      |
## |        **SEX (%)**        | Female |       6 (21.4)        |       14 (51.9)        | 0.039  |      |
## |                           |  Male  |       22 (78.6)       |       13 (48.1)        |        |      |
## |  **V1.Age (mean (SD))**   |        |     39.39 (13.77)     |     39.56 (13.98)      | 0.965  |      |
## |  **MEL_cat (mean (SD))**  |        |      3.52 (1.60)      |      4.33 (1.05)       | 0.049  |      |
## |    **INR (mean (SD))**    |        |      3.35 (2.79)      |      4.37 (2.10)       | 0.180  |      |
## | **zipIncome (mean (SD))** |        |  53477.39 (18001.70)  |  57480.76 (15744.99)   | 0.439  |      |
## |   **SES1 (mean (SD))**    |        |     -0.40 (2.06)      |      0.62 (1.76)       | 0.054  |      |
## |   **SES2 (mean (SD))**    |        |     -0.27 (0.34)      |      -0.17 (0.27)      | 0.244  |      |
## | **ExpLang_T (mean (SD))** |        |     31.67 (11.07)     |     49.78 (11.10)      | <0.001 |      |
## | **RecLang_T (mean (SD))** |        |     32.32 (11.85)     |     53.85 (10.96)      | <0.001 |      |
## |  **ELC_SS (mean (SD))**   |        |     71.96 (20.00)     |     105.67 (15.78)     | <0.001 |      |
## |    **TBV (mean (SD))**    |        | 1077031.79 (96937.48) | 1050164.41 (111924.89) | 0.345  |      |
## 
## Table: Participant Summary Table for Q>=4

Participant Table, Q>=3

## 
## 
## |          &nbsp;           | level  |          ASD           |           TD           |   p    | test |
## |:-------------------------:|:------:|:----------------------:|:----------------------:|:------:|:----:|
## |           **n**           |        |           36           |           31           |        |      |
## |        **SEX (%)**        | Female |       10 (27.8)        |       14 (45.2)        | 0.221  |      |
## |                           |  Male  |       26 (72.2)        |       17 (54.8)        |        |      |
## |  **V1.Age (mean (SD))**   |        |     39.03 (12.95)      |     37.61 (14.20)      | 0.671  |      |
## |  **MEL_cat (mean (SD))**  |        |      3.54 (1.50)       |      4.36 (0.99)       | 0.019  |      |
## |    **INR (mean (SD))**    |        |      3.46 (2.75)       |      4.13 (2.14)       | 0.319  |      |
## | **zipIncome (mean (SD))** |        |  54158.10 (18734.17)   |  56118.68 (15004.41)   | 0.675  |      |
## |   **SES1 (mean (SD))**    |        |      -0.35 (1.97)      |      0.54 (1.66)       | 0.053  |      |
## |   **SES2 (mean (SD))**    |        |      -0.25 (0.35)      |      -0.19 (0.26)      | 0.427  |      |
## | **ExpLang_T (mean (SD))** |        |     32.62 (11.76)      |     48.77 (11.52)      | <0.001 |      |
## | **RecLang_T (mean (SD))** |        |     32.49 (12.52)      |     53.32 (11.13)      | <0.001 |      |
## |  **ELC_SS (mean (SD))**   |        |     72.23 (19.97)      |     104.94 (16.57)     | <0.001 |      |
## |    **TBV (mean (SD))**    |        | 1076827.78 (100384.08) | 1045805.34 (115665.34) | 0.244  |      |
## 
## Table: Participant Summary Table for Q>=3

Bivariate Correlation Plots, ASD&TD Together, Q>=4

Bivariate Plot

Bivariate Plot

Bivariate Correlation ASD and TD, Q>=3

Bivariate Plot

Bivariate Plot

Bivariate correlations, ASD Only, Q>=4

Bivariate Plot ASD Only

Bivariate Plot ASD Only

Bivariate correlations, ASD Only, Q>=3

Bivariate Plot ASD Only

Bivariate Plot ASD Only

Bivariate correlations, TD Only Q>=4

Bivariate Plot, TD Only

Bivariate Plot, TD Only

Bivariate correlations, TD Only Q>=3

Bivariate Plot, TD Only

Bivariate Plot, TD Only

LGI Results, compare results for data quality Q>=4 vs. data quality Q>=3, Regression Models: INR

INR Results Q>=4

  rh_parsopercularis_lgi
Coeffcient Estimates CI (95%) p-Value
Intercept 3.48 2.46 – 4.50 <0.001
Income:Needs 0.04 0.01 – 0.08 0.026
TBV 0.00 -0.00 – 0.00 0.125
Age 0.01 0.00 – 0.02 0.027
Observations 42
R2 / R2 adjusted 0.342 / 0.290

Income to needs ratio predicts rh_parsopercularis_lgi, controlling for age and TBV (dx, sex, and age not sig. predictors)

INR Results Q>3

  rh_parsopercularis_lgi
Coeffcient Estimates CI (95%) p-Value
Intercept 3.74 2.91 – 4.58 <0.001
Income:Needs 0.03 0.00 – 0.07 0.045
TBV 0.00 -0.00 – 0.00 0.144
Age 0.01 0.00 – 0.01 0.031
Observations 52
R2 / R2 adjusted 0.289 / 0.244

Income to needs ratio predicts rh_parsopercularis_lgi, controlling for age and TBV (dx, sex, and age not sig. predictors)

LGI Results, compare restuls for data quality Q>=4 vs. data quality Q>=3, Regression Models SES1

Neighborhood Advantage Results Q>=4

Neighborhood Advantage not a significant predictor of LGI when controlling for TBV and dx for Q>=4.

Neighborhood Advantage Results Q>3

Neighborhood Advantage not a significant predictor of LGI when controlling for TBV and dx for data Q>=3.

LGI Results, compare restuls for data quality Q>=4 vs. data quality Q>=3, Regression Models SES2

Neighborhood Disadvantage Results Q>=4

Neighborhood Disdvantage is a significant predictor of lh-middle temporal LGI and rh-transverse temporal when controlling for TBV and age for Q>=4. There is not a significant SES2xDx Interaction (dx main effect also not significant). This indicates that higher disadvantage is associated with higher LGI (primarily in the TD group). This finding is in a different direction than those with INR.

  lh_middletemporal_lgi
Coeffcient Estimates CI (95%) p-Value
Intercept 2.90 2.40 – 3.40 <0.001
SES2 0.16 0.01 – 0.31 0.039
TBV 0.00 0.00 – 0.00 0.008
Age 0.00 -0.00 – 0.01 0.467
Observations 55
R2 / R2 adjusted 0.299 / 0.257

Neighborhood Disadvantage Results Q>=3

Neighborhood Disadvantage is not a significant predictor of LGI when controlling for TBV and dx for data q >=3.

  lh_middletemporal_lgi
Coeffcient Estimates CI (95%) p-Value
Intercept 3.04 2.60 – 3.48 <0.001
SES2 0.13 -0.01 – 0.26 0.072
TBV 0.00 0.00 – 0.00 0.011
Age 0.00 -0.00 – 0.00 0.534
Observations 66
R2 / R2 adjusted 0.232 / 0.195

LGI Results, compare results for data quality Q>=4 vs. data quality Q>=3, Regression Models MEL

MEL Results Q>=4

Maternal Education not a significant predictor of LGI when controlling for TBV and dx for data Q>=4.

MEL Results Q>=3

Maternal Education not a significant predictor of LGI when controlling for TBV and dx for data Q>=3.

LGI Results, compare restuls for data quality Q>=4 vs. data quality Q>=3, Regression Models ZipIncome

Zip-Income Results, data Q>=4

Zip-Income is a significant predictor when controlling for TBV. Removed Age and Dx from models since they were not significant.

  lh_parsorbitalis_lgi
Coeffcient Estimates CI (95%) p-Value
Intercept 2.20 1.50 – 2.89 <0.001
Zip-Income 0.00 0.00 – 0.00 0.020
TBV 0.00 -0.00 – 0.00 0.151
Age 0.00 -0.00 – 0.01 0.182
Observations 55
R2 / R2 adjusted 0.296 / 0.255

Zip-Income Results Q>=3

Zip-Income is a significant predictor of lh-pars orbitals LGI, when controlling for TBV and age, for Q>=3.

  lh_parsorbitalis_lgi
Coeffcient Estimates CI (95%) p-Value
Intercept 2.20 1.50 – 2.89 <0.001
Zip-Income 0.00 0.00 – 0.00 0.020
TBV 0.00 -0.00 – 0.00 0.151
Age 0.00 -0.00 – 0.01 0.182
Observations 55
R2 / R2 adjusted 0.296 / 0.255

LGI Results, compare results for data quality Q>=4 vs. data quality Q>=3, Regression Models: Dx

Dx Results, Q>=4

Dx predicts left hemisphere pars triangularis and right hemisphere middle temporal LGI, when controlling for TBV, age, and sex (the latter were not sig. predictors or RH MTG LGI, so removed from the model).

  lh_parstriangularis_lgi
Coeffcient Estimates CI (95%) p-Value
Intercept 3.26 2.51 – 4.01 <0.001
Dx -0.15 -0.29 – -0.01 0.034
TBV 0.00 0.00 – 0.00 0.001
Sex -0.18 -0.35 – -0.01 0.038
Observations 55
R2 / R2 adjusted 0.234 / 0.189
  rh_middletemporal_lgi
Coeffcient Estimates CI (95%) p-Value
Intercept 2.29 1.83 – 2.76 <0.001
Dx 0.09 0.01 – 0.18 0.035
TBV 0.00 0.00 – 0.00 <0.001
Observations 54
R2 / R2 adjusted 0.393 / 0.369

Dx Results, Q>=3

Diagnosis not associated with LGI in the Q>=3 dataset (after removing SES variables from the model).

  lh_parstriangularis_lgi
Coeffcient Estimates CI (95%) p-Value
Intercept 3.26 2.51 – 4.01 <0.001
Dx -0.15 -0.29 – -0.01 0.034
TBV 0.00 0.00 – 0.00 0.001
Sex -0.18 -0.35 – -0.01 0.038
Observations 55
R2 / R2 adjusted 0.234 / 0.189
  rh_middletemporal_lgi
Coeffcient Estimates CI (95%) p-Value
Intercept 2.29 1.83 – 2.76 <0.001
Dx 0.09 0.01 – 0.18 0.035
TBV 0.00 0.00 – 0.00 <0.001
Observations 54
R2 / R2 adjusted 0.393 / 0.369

LGI Results, compare results for data quality Q>=4 vs. data quality Q>=3, Regression Models: Sex/Gender

Sex/Gender Results, Q>=4

Sex predicts lh pars opercularis LGI, controlling for TBV, dx, and age

  lh_parsopercularis_lgi
Coeffcient Estimates CI (95%) p-Value
Intercept 3.28 2.43 – 4.12 <0.001
Sex -0.19 -0.38 – -0.00 0.046
Dx -0.14 -0.29 – 0.01 0.062
Age 0.00 -0.00 – 0.01 0.247
TBV 0.00 0.00 – 0.00 0.001
Observations 55
R2 / R2 adjusted 0.376 / 0.326

Sex Results Q>=3

Sex predicts lh pars opercularis LGI, controlling for TBV, dx, and age

  lh_parsopercularis_lgi
Coeffcient Estimates CI (95%) p-Value
Intercept 3.27 2.57 – 3.96 <0.001
Sex -0.17 -0.32 – -0.03 0.018
Dx -0.14 -0.27 – -0.01 0.030
Age 0.00 -0.00 – 0.01 0.200
TBV 0.00 0.00 – 0.00 <0.001
Observations 67
R2 / R2 adjusted 0.438 / 0.402